Influencers Understand Your Customers Far Beyond Demographics

Marketers can look forward to a time when influencers pave the way to a more sophisticated targeting strategy based on strong bonds of interest, rather than merely demographics.

Do you like alternative music? Cool. But what do you mean by “alternative music”? Is it Nickelback or Parquet Courts? Or do you believe that Kendrick Lamar is alternative? Or are you instead drawn to the more mellow sounds of Joanna Newsom or Sufjan Stevens? Or do you like all of that stuff and believe that one shouldn’t be doctrinaire, but enjoy all music on its own terms?

When you’re targeting your advertising, these nuances matter, too. If Consumer X falls under the heading of “alternative music fan” and you serve him up an ad with a Matchbox Twenty tune, then it might backfire, big time. Let’s not even contemplate what it would be like to show “alternative” Millennials a Nickleback ad.

For applicable reasoning, let’s go back to Robert Putnam’s seminal 2000 work “Bowling Alone: The Collapse and Revival of American Community.” Putnam, a political scientist, surveyed the nation at the turn of the century and surmised that Americans had turned their backs on the kinds of social organizations that had sustained them in years past.

Membership in community organizations, such as rotary clubs, garden societies, book clubs, and PTAs, was all on the decline. Rather than belonging to a bowling team, for instance, many lived atomized existences defined by the living room and TV. This was before the internet had really hit mainstream America.

The strange thing is that as Americans became less connected at the community level, they became more connected through decentralized organizations. Instead of those close-knit groups like bowling leagues, Americans increasingly belonged to organizations like the AARP that were so big and broadly defined that membership was practically meaningless. A member of the AARP likely never met other members; the ties that bound them together were thin and ephemeral at best.

I’d wager that Putnam’s distinction between these two kinds of groups—the one that is based on deep, intentional membership and interaction with other members of the group, and the other that is based on flimsy, nominal membership without any interaction with other members—provides a useful guide to audience targeting in an era defined by the rise of programmatic and the dominance of social platforms.

It’s useful because each of us are a bit of both. We are members of mainstream demographic groups, and demographics such as age, gender, location, and income level do give some solid indications as to our preferences. But all of us also maintain passions and interests that don’t necessarily map to our demographic profiles. The internet is home to both kinds of groups listed above: the personal and the impersonal. There is behavioral data to indicate both kinds of interests. Knowing how to identify, navigate, and properly message to them is the key.

Ties That Bind

Traditional data segmentation is based on mainstream demographics. The premise of this type of targeting rests on a presumption of equivalence: the idea that people in the same age groups, of the same gender, and of the same income level are likely to think (and shop) roughly the same way.

This broad-brush approach works to a certain extent. Suburban homeowners aged 34 to 49 are much more likely to be interested in buying a barbecue at some point than your 24- to 35-year-old urbanite. However, there are obvious limitations to this approach. Namely, that not every white 29-year-old woman in San Francisco, not every sports fan in Chicago, and not every Latina mother in North Carolina is going to care about the same stuff.

Digital advertising has always promised to solve that problem. Tapping into deeply held passions is key for marketers that are aiming to create one-on-one dialogues with consumers. It’s the key to that moment where consumers feel that a brand really “gets” him or her.

But such targeting requires more than just added precision, and it begs a more rigorous approach than merely grouping consumers into large pools.

That’s why marketers should take a page from Putnam’s book and realize that not all groups are created equal. Look through the data to identify which groups a consumer feels the strongest membership toward and which groups ask for membership that is merely circumstantial. That’s the difference between an ad that’s just seen by the right person and an ad that really makes an impression on that person.

Social Graph To The Rescue?

Social media seems to be the obvious answer to this question of finding real groups. After all, Facebook knows who your friends are! But in reality, Facebook itself is so large that both forms of membership exist on the platform, both meaningful and nonmeaningful.

Looking deeper, it’s the influencers on social platforms that give marketers the most turnkey method for accessing online communities bound by strong ties of common interest. Even though their audiences might be small (10,000 to 50,000 followers), these influencers likely understand their audiences better than marketers and better than what marketers could glean through all manner of demographic number-crunching.

They have the qualitative hook and the aesthetic discipline that comes from real membership in the communities that form around them. Whether a consumer follows an influencer is a better indicator of the person’s real interests than the pages the consumer “likes,” and the messages that come via that influencer are likely to have all the more influence as a result.

Influencer marketing is currently in the midst of a sudden and rapid evolution toward scalability and programmatic activation. We are nearing the point where audience data from influencer marketing programs becomes more portable and more actionable through platforms outside the walled gardens themselves.

When it does, marketers can look forward to a time when influencers pave the way to a more sophisticated targeting strategy based on strong bonds of interest, not the presumed equivalence of demographics.